Journals / Muhasebe ve Finansman Dergisi (. e-Muhasebe ve Finansman Dergisi) / 2010 / Cilt: 0 - Sayı: 48

The relationship between return volatility and trading volume: An empirical study in the ISE

Getiri volatilitisi ile işlem hacmi arasındaki ilişki: İMKB'de ampirik bir çalışma

Pages
200–216
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With the VAR model, it was concluded that there is a long-term, negative relation from trading volume to volatility.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the relation between return volatility and trading volume in the ISE National 100 Index was examined by making use of monthly data in the period between 1997 and 2009.
📊
Key Findings & Data:First of all the existence of volatility was proven with ARCH test, and then generalized autoregressive conditional heteroscedasticity (GARCH) model was used to model volatility.
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Conclusion & Impact:With the VAR model, it was concluded that there is a long-term, negative relation from trading volume to volatility.
🔬Design:Modeling & Simulation
📍Scope:2009 Verileri
⚙️Variables:Domain Parameters

Abstract

In this study, the relation between return volatility and trading volume in the ISE National 100 Index was examined by making use of monthly data in the period between 1997 and 2009. First of all the existence of volatility was proven with ARCH test, and then generalized autoregressive conditional heteroscedasticity (GARCH) model was used to model volatility. To examine the relation between return volatility and trading volume, unstructured VAR method was applied. Moreover, Granger causality test was used to determine bilateral relation. With the VAR model, it was concluded that there is a long-term, negative relation from trading volume to volatility. Besides, the findings of the study also revealed bilateral Granger causality relation between return volatility and trading volume. These findings indicate that Sequential Arrival Information and Mixed Distribution Hypothesis are not valid for the ISE.

Özet

Bu çalışmada, 1997- 2009 dönemi aylık veriler kullanılarak İMKB Ulusal 100 Endeksinin getiri vola-tilitesi ile işlem hacmi arasındaki ilişki incelenmiştir. Çalışmada öncelikle volatilitenin varlığı ARCH testi ile ortaya konmuş, daha sonra volatiliteyi modellemek üzere genelleştirilmiş otoregresif koşullu değişen varyans (GARCH) modelinden yararlanılmıştır. Getirinin volatilitesi ile işlem hacmi arasındaki ilişkiyi incelemek amacıyla yapısal olmayan VAR yöntemi uygulanmıştır. Ayrıca çift taraflı ilişkiyi tespit edebilmek üzere Granger nedensellik testi de yapılmıştır. Kurulan VAR modeli ile değişkenler arasında uzun dönemli, işlem hacminden volatiliteye doğru negatif yönlü ilişkinin varlığı tespit edilmiştir. Ayrıca çalışma bulguları, getirinin volatilitesi ile işlem hacmi arasında iki yönlü Granger nedensellik ilişkisini ortaya koymuştur. Bu bulgular, İMKB'de Ardışık Bilgi Akışı ve Karışık Dağılımlar Hipotezlerinin geçerli olmadığına işaret etmektedir.

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Cite This Article

GÜVENEK, B., ACAR, M. B., ALPTEKİN, V. (2022). The relationship between return volatility and trading volume: An empirical study in the ISE. Muhasebe ve Finansman Dergisi (. e-Muhasebe ve Finansman Dergisi), Cilt: 0 - Sayı: 48, 200–216. https://ajindex.com/articles/582615

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References (1)

  1. Ahmed, H. J. A., Hassan, A., ve Nasir A. M. D. (2005). The Relationship between Trading Volume, Volatility and Stock Market Returns: A Test of Mixed Distribution Hypothesis for a Pre and Post Crisis on Kuala Lumpur Stock Exchange, Investment Management and Financial Innovations. 3:146-158. 2.Akar, C. (2008). Yabancılar Türkiye'de Pozitif Geri Besleme Hipotezine Uygun Davranışlar Gösterirler Mi?, İMKB Dergisi. 10 (39): 61-67. 3.Andersen, T. G. (1996). Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic volatility, The Journal of Finance. 51 (1): 169-204. 4.Asai, M. ve Unite, A. (2008). The Relationship between Stock Return Volatility and Trading Volume: The Case of The Philippines, Applied Financial Economics. 18(16): 1333-1341. 5.Badhani, K. N. (2005). Stock Price-Volume Causality at Index Level, Indian Institute of Capital Markets 9th Capital Markets Conference Paper, http://papers.ssrn.com/sol3/papers.cfm7abstract_i d=874914. 6.Baklacı, H. ve Kasman A. (2006). An Empirical Analysis of Trading Volume and Return Volatility Relationship in The Turkish Stock Market, Ege Academic Review. 6 (2): 115-125. 7.Başçı, E., Özyıldırım, S. ve Aydoğan, K. (1996). A Note on Price-Volume Dynamics in An Emerging Stock Market, Journal of Banking and Finance. 20 (2): 389-400. 8.Bayrakdaroğlu, A. ve Nazlıoğlu, Ş. (2009). Hisse Senedi Fiyat-Hacim İlişkisi: İMKB'de İşlem Gören Bankalar İçin Doğrusal' ve Doğrusal Olmayan Granger Nedensellik Analizi, İktisat İşletme ve Finans Dergisi. 24 (277): 85-109. 9.Bohl, M. T. ve Henke, H. (2003). Trading Volume and Stock Market Volatility: The Polish Case, International Review of Financial Analysis. 12 (5): 513-525. 10.Bollerslev, T. (1986). Generalized Autore-gressive Conditional Heteroskedasticity, Journal of Econometrics. 31: 307 - 327- 11.Brailsford, T. J. (1996). The Empirical Relationship between Trading Volume, Returns, and Volatility, Accounting and Finance. 35: 89-111. 12.Brooks, C. (1998). Predicting Stock Index Volatility: Can Market Volume Help?, Journal of Forecasting. 17 (1): 59-80. 13.Chen, G., Firth, M. ve Rui, O. M. (2001). The Dynamic Relation Between Stock Returns, Trading Volume and Volatility, Financial Review. 36:153-173. 14.Clark, P. K. (1973). A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices, Econometrica. 41:135-155. 15.Copeland, T. E. (1976). A Model of Asset Trading Under the Assumption of Sequential Information Arrival, Journal of Finance